(a) Field of the Invention
The present invention relates to a method for detecting block edges from DCT (Discrete Cosine Transform)-compressed images and classifying the edge direction of each block. More specifically, the present invention relates to a method for receiving a DCT-compressed image, recovering DCT coefficients through partial decoding, detecting the edge of each block according to the results of minimal arithmetic operations in the DCT domain without IDCT (Inverse Discrete Cosine Transform), and if any, classifying the edge direction of each block.
(b) Description of the Related Art
The conventional technologies for detecting the edge direction of each block from an image have been described in the related documents as follows.
“Image Vector Quantizer Based on a Classification in the DCT Domain” (IEEE Transactions on Communications, Vol. 39, No. 4, April 1991) by D. S. Kim and S. U. Lee in 1991 discloses a method for detecting and classifying the edge of each block to be quantized so as to improve performance in encoding an image using vector quantization. In this method, a block edge classifier is required to be trained in advance using some image data having an actual block edge component in order to classify the edge of each block. The DCT domain is divided according to the directional component of each edge, and with given DCT coefficients, the directional component of the block edge is determined based on which division the DCT coefficients fall on. This method can be implemented very simply without the IDCT step in classifying the edge component of each block in images, but the performance is greatly dependent upon the training data because it is an inductive method.
“Efficient Use of MPEG-7 Edge Histogram Descriptor” (ETRI Journal, Vol. 24, No. 1, February 2002) by C. S. Won et al. in 2001 proposed a method of classifying the edge direction of each block as well as a method of applying information about edge direction of each block to the retrieval of images. But, the proposed method, which is performed in the pixel domain, requires IDCT for an input DCT-compressed image, increasing the computational load.